CN102788704A - Automobile operation stability testing system based on driver model and testing method - Google Patents
Automobile operation stability testing system based on driver model and testing method Download PDFInfo
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Abstract
The invention provides an automobile operation stability testing system based on a driver model and an automobile operation stability testing method. The driver model comprises a pre-scanning module, a pre-testing module, a comparing module and a control module, wherein the pre-scanning module obtains an anticipating track according to output of a trailing sensor installed on an automobile, the pre-testing module calculates a pre-testing track of automobile running according to output of a sensor inside the automobile, the comparing module enables the anticipating track and the pre-testing track to be compared and outputs deviation, and the control module calculates and outputs changing quantity of steering wheel corners through potential difference (PD) control according to the deviation. The anticipating track is a snakelike path on an automobile running path, the automobile runs around stakes along the snakelike path at setting speed, the testing system and the testing method calculate final steering wheel corners and output to the automobile to control the automobile to track the anticipating track to run according to the steering wheel corners obtained from automobile status information and the changing quantity of the steering wheel corners calculated by the driver model, and therefore, the automobile operation stability is tested.
Description
Technical field
The present invention relates to a kind of vehicle handling stability detection system and detection method based on pilot model; To detect vehicle handling stability; Specifically; Relate to a kind of pilot model that utilizes and replace experienced driver to control tested automobile, thus the vehicle handling stability detection system and the detection method of testing automobile control stability.
Background technology
Along with modern development in science and technology, people are increasing for the demand of automobile, and private car is also more and more universal.This demand has greatly stimulated automobile market, makes more and more enterprises invest in automobile making.A large amount of emerging in large numbers of automobile also make traffic safety problem become serious day by day, and except guaranteeing safe driving through formulating various traffic laws, the handling safety of automobile itself also more and more receives publicity.Each new car all will carry out various tests before dispatching from the factory, wherein just comprise the control stability of testing automobile, to guarantee the handling safety of automobile itself.And very heavy and loaded down with trivial details beyond doubt to the detection of these automobiles, inevitable fatigue state all can cause abnormal detection in detection workman's skill level, technical capability and the course of work, thereby possibly cause the potential safety hazard of automobile itself.
Exist open loop detection and closed loop to detect two kinds of vehicle handling stability detection methods in the prior art.In open loop detects, preset to the input (bearing circle, throttle and brake signal are over time) of tested automobile, do not rely on the response of automobile; In closed loop detects, then require tested automobile to go, and guarantee that trajectory track is in certain error range along preset track.In open loop detects, can handle automobile with robot, the repetition high conformity of detection, but the bearing circle input does not rely on the response of automobile; In closed loop detects,, can not embody people's driving performance and limitation well though also can adopt robot to handle.So in the vehicle handling stability of reality detects, generally handle tested automobile, accomplish various testing schemes by experienced driver.But; Because causing testing, test speed generally higher (80km/h or more than) has certain danger; And in test process repeatedly; Even if experienced driver can not guarantee each in full accord to the input of tested automobile, will introduce the input influence for the control stability of systematic analysis automobile, thereby can not estimate vehicle handling stability objectively.
Summary of the invention
The detection method that the purpose of this invention is to provide a kind of new vehicle handling stability.In detection method of the present invention, utilize pilot model to replace experienced driver to control tested automobile, through the parameter of pilot model is set; Not only can emulation the driver of different driving styles; Feasible detection is more comprehensive, reliable, and for the driver of specific driving style, pilot model can guarantee that the repeated detection process is consistent to the input of tested automobile; Avoided the influence of input to system stability; Make and improve the duplicate detection high conformity result's confidence level, and alleviated testing staff's work load greatly.
According to one object of the present invention, a kind of vehicle handling stability detection system based on pilot model is provided, be used to detect vehicle handling stability; Said detection system comprises: tracing sensor; Be installed on the automobile, be used to carry out Path Recognition, and the output expected trajectory; The automotive interior sensor obtains and exports vehicle condition information; Pilot model; Comprise and take aim at module, prediction module, comparison module and control module in advance that take aim at module in advance and obtain expected trajectory according to the output that is installed in the tracing sensor on the automobile, prediction module is according to the vehicle condition information of automotive interior sensor output; Calculate the prediction locus of running car; Comparison module compares expected trajectory and prediction locus, output bias, and control module is calculated the change amount of outbound course dish corner through PD control according to said deviation; Wherein, Expected trajectory is the serpentine path on the running car path, and automobile goes around stake along serpentine path according to setting speed, and said detection system is according to the change amount of the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model; Calculate final steering wheel angle and export to automobile, follow the trail of expected trajectory with Control of Automobile and go; Controller; Receive final steering wheel angle signal, export the signal corresponding with the control controlled device according to said final steering wheel angle signal, thereby accomplish corresponding operating each parts of automobile with the controlled device of automobile; Following the trail of expected trajectory with Control of Automobile goes; Obtain the status information of automobile after under the control of controller, operating through the automotive interior sensor, and said status information is fed back to pilot model, with the closed-loop control of realization automobile.
The speed of said setting guarantees that automobile can not roll serpentine path away from and in testing process, keep constant in a detection circulation.
According to another object of the present invention; A kind of vehicle handling stability detection method based on pilot model is provided; Be used to detect vehicle handling stability; Said detection method comprises: automobile according to the speed of setting when expected trajectory goes, be installed in tracing sensor dynamic scan on the automobile to obtain the expected trajectory information of automobile, the automotive interior sensor also writes down vehicle condition information; Tracing sensor and automotive interior sensor and pilot model communicate, so that expected trajectory information and vehicle condition information are input to pilot model; Pilot model is from the prediction locus of vehicle condition information acquisition running car, expected trajectory and prediction locus compared obtain deviation; Pilot model utilizes said deviation to calculate the change amount of outbound course dish corner through PD control; Said detection method is calculated final steering wheel angle according to the change amount of the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model, and final steering wheel angle signal is input to controller; Controller is exported the signal corresponding with controlled device with Control of Automobile according to said final steering wheel angle signal; Thereby accomplish corresponding operating, follow the trail of expected trajectory with Control of Automobile and go, detect vehicle handling stability thus each parts of automobile; Wherein, Pilot model comprises takes aim at module, prediction module, comparison module and control module in advance, takes aim at module in advance and obtains expected trajectory according to the output that is installed in the tracing sensor on the automobile, and prediction module is according to the vehicle condition information of automotive interior sensor output; Calculate the prediction locus of running car; Comparison module compares expected trajectory and prediction locus, output bias, and control module is calculated the change amount of outbound course dish corner through PD control according to said deviation; Expected trajectory is the serpentine path on the running car path, and automobile goes around stake along serpentine path according to the speed of setting.
Said method also comprises: before tracing sensor and automotive interior sensor began to detect, each sensor of initialization and controller were removed the data in each sensor, and the input/output port and the register of controller is set.
Said method also comprises: before tracing sensor and automotive interior sensor begin to detect; Initialization clock and pilot model, the time that makes enabling time and the automobile of beginning sampling time, controller and pilot model of each sensor get into serpentine path keeps synchronously.
Said method also comprises: after controller output control signal, and the change amount of storage direction dish corner in pilot model and/or controller.
Said method also comprises: in pilot model and/or controller, after the change amount of storage direction dish corner, determine whether to accomplish the required detection-comparison-control procedure of control that tracks.
Said method also comprises: if accomplished detection-comparison-control procedure, then finish the detection to vehicle handling stability; If do not accomplish detection-comparison-control procedure, then continue to carry out detection-comparison-control procedure.
Description of drawings
Fig. 1 is the synoptic diagram according to pilot model of the present invention.
Fig. 2 is the synoptic diagram according to the vehicle handling stability detection system of the pilot model based on Fig. 1 of the present invention.
Fig. 3 is the synoptic diagram according to the vehicle handling stability detection method of the pilot model based on Fig. 1 of the present invention.
Fig. 4 is the synoptic diagram that is used for the snakelike test road of vehicle handling stability detection method.
Embodiment
Describe in detail with reference to the accompanying drawings according to pilot model of the present invention, based on the vehicle handling stability detection system and the detection method of pilot model.
In the present invention, in order to simplify description, be to carry out based on the vehicle handling stability detection system and the detection method of pilot model, but the invention is not restricted to this that automobile can go along free routing to automobile in snakelike test travels down.
Fig. 1 is the synoptic diagram according to pilot model of the present invention.
The present invention utilizes pilot model to substitute experienced driver; Can not only guarantee that pilot model is consistent to the input of automobile in the repeated detection process; And can alleviate testing staff's working load; Avoid the generation of security incident, this pilot model can embody people's driving performance and limitation simultaneously.Can be in pilot model through the driver's (for example, experienced driver, radical driver etc.) that different parameter values obtains different driving styles driving performance is set.
In addition, pilot model according to the present invention is based upon on the existing queuing network cognition system, according to people's driving performance pilot model is divided into three parts: perception part, cognitive part and motion parts.When this pilot model Control of Automobile was followed the trail of expected trajectory, it is the true driver's of emulation driving performance and physiology limitation exactly, but the invention is not restricted to this, and pilot model can pass through nextport hardware component NextPort (for example, robot) to be realized.
Specifically, as shown in Figure 1, pilot model according to the present invention comprises takes aim at module, prediction module, comparison module, control module etc. in advance.Take aim at module in advance and obtain expected trajectory according to the output that is installed in the tracing sensor on the automobile.Prediction module is calculated the prediction locus of running car according to the vehicle condition information (for example, yaw angle, side direction coordinate, along slope coordinate, side velocity, longitudinal velocity, side acceleration, longitudinal acceleration etc.) of automotive interior sensor output.Comparison module compares expected trajectory and prediction locus, parameters (in the present invention, comprising lateral position deviation R, side acceleration, side acceleration derivative etc.) such as acquisition and output bias.Control module is calculated the also change amount of outbound course dish corner that obtains according to said deviation through PD control.
At last; Based on the detection system of pilot model and detection method change amount according to the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model; Calculate final steering wheel angle and export to automobile (more particularly, exporting to the controller (for example, single-chip microcomputer) of detection system); Follow the trail of expected trajectory with Control of Automobile and go, this will be discussed in more detail below.
Here, expected trajectory is the road information of running car, that is, and and above-described snakelike test road.Describe in order further to simplify, in the present invention, with the snakelike test road among the GB/T 6323.1-94 as an example.As shown in Figure 4; A plurality of stakes 41 are arranged on equal intervals ground in the running car path, and the distance of asking of two adjacent stakes 41 is L, on the center line of driving path, indicate expected trajectory 42 (promptly with the adhesive tape that is different from the road color; Serpentine path is shown in dotted line).The effective stake district (that is, needing Control of Automobile) that is used for the testing automobile control stability along zone that serpentine path is gone at second stake to the serpentine path between the penult stake.For the ease of describing, the XY coordinate axis has been shown in Fig. 4.
It is following in pilot model, to obtain lateral position deviation R, side acceleration, the isoparametric process of side acceleration derivative:
The module of taking aim in advance in the pilot model is being taken aim at time (T in advance through tracing sensor acquisition automobile
p) interior expected trajectory point P
n(x
n, y
n), wherein, x
nExpression is along the coordinate of serpentine path traveling automobile at directions X, y
nExpression is along the coordinate of serpentine path traveling automobile in the Y direction.Prediction module in the pilot model obtains the current state S of automobile through the automotive interior sensor
n(x
n, y
n, a
x, a
y) and dope automobile and taking aim at time (T in advance
p) in the position coordinates family P ' that will arrive
n(x '
n, y '
n), wherein, a
xExpression is along the acceleration of serpentine path traveling automobile at directions X, a
yExpression is along the acceleration of serpentine path traveling automobile in the Y direction.Just can obtain the lateral position deviation R of expected trajectory and prediction locus thus.
R
n＝y′
n-y
n (1)
By formula (1), the lateral position deviation in n step deducts the side direction coordinate of expected trajectory point through the side direction coordinate of prediction locus point.
In order accurately to follow the trail of expected trajectory, will adjust steering wheel angle to reduce lateral position deviation R.The change amount of in pilot model, utilizing PD to control to obtain steering wheel angle.The formula that when utilizing the change amount of pilot model acquisition steering wheel angle, relates to is following:
ΔΦ
n＝k
p·a
yn+k
d·a′
yn (4)
Φ
n＝Φ′
n-1+ΔΦ
n (5)
By formula (2), obtain n step side velocity v according to the automotive interior sensor
n, calculate the side acceleration a that arrives desired location
Yn
By formula (3), can obtain the derivative a ' of n step side acceleration divided by the time of taking aim in advance through the difference of n step side acceleration and n-1 step side acceleration
Yn
By formula (4), through PD control, obtain the change amount of steering wheel angle, can (for example, work as k through the driver of the different driving styles of emulation in addition
p=0.008, k
d=-0.02 o'clock, can the emulation experienced driver; And bigger k
pAnd k
dThen can the radical driver of emulation, otherwise, then can the conservative driver of emulation.), detect the dynamic performance of automobile under limiting condition, for better assessing the automobile characteristic foundation is provided.
At last, by formula (5), the steering wheel angle in n-1 step adds that the change amount of steering wheel angle just can obtain final steering wheel angle.
Like this; Through calculating the final steering wheel angle signal input controller (as shown in Figure 2) that obtains; Controller according to said final steering wheel angle signal output be installed on the automobile controlled device (for example; Steer motor, speed motor) corresponding signal is with the control controlled device, and follow the trail of expected trajectory with Control of Automobile and go.
In addition, based on the detection system of pilot model and detection method also according to the relatively acquisition of expected trajectory and prediction locus and export other control signals (for example, accelerator open degree, brake aperture etc.).Controller receive these control signals and according to the corresponding signal of these control signals outputs and controlled device (for example, steer motor, speed motor etc.) with the control controlled device, thereby accomplish corresponding operating to each parts of automobile, this will be discussed in more detail below.
Fig. 2 is the synoptic diagram according to the vehicle handling stability detection system based on pilot model of the present invention.
As shown in Figure 2; Vehicle handling stability detection system based on pilot model according to the present invention is used to detect vehicle handling stability; Said detection system comprises tracing sensor, automotive interior sensor, pilot model, controller (for example, single-chip microcomputer) etc.Tracing sensor is installed on the automobile, is used to carry out Path Recognition, and output expected trajectory (for example, road information).The automotive interior sensor obtains and exports vehicle condition information (for example, yaw angle, side direction coordinate, along slope coordinate, side velocity, longitudinal velocity, side acceleration, longitudinal acceleration etc.).Pilot model (for example receives; Change through A/D) expected trajectory and vehicle condition information; Prediction locus from vehicle condition information calculations running car; Expected trajectory and prediction locus are compared parameters (in the present invention, lateral position deviation R, side acceleration, side acceleration derivative etc.) such as acquisition and output bias, calculate the change amount of acquisition and outbound course dish corner according to said deviation through PD control.Based on the detection system of pilot model change amount, calculate final steering wheel angle and export to automobile according to the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model.Controller receives final steering wheel angle signal; According to said final steering wheel angle signal output and controlled device (for example; Steer motor, speed motor etc.) corresponding signal is with the control controlled device; Thereby accomplish corresponding operating, follow the trail of expected trajectory with Control of Automobile and go each parts of automobile.
At last, obtain the status information of automobile after under the control of controller, operating, and said status information is fed back to pilot model, with the closed-loop control of realization automobile through the automotive interior sensor.
Because how pilot model obtains deviation and when describing Fig. 1, describes in detail according to the process that said deviation obtains final steering wheel angle, so no longer be repeated in this description at this.
Fig. 3 is the synoptic diagram according to the vehicle handling stability detection method based on pilot model of the present invention.
As shown in Figure 3, the vehicle handling stability detection method based on pilot model according to the present invention is used to detect vehicle handling stability, said method comprising the steps of.
In step 301, the detection of beginning vehicle handling stability.Before beginning to detect, need to detect the duty of automobile component, and whether detect each sensor (for example, be installed on the automobile tracing sensor and automotive interior sensor) in proper working order.After inspection finishes; The interface of each sensor is connected with computing machine through A/D modular converter (not shown in figures), and the drive motor of computing machine through controller (for example, single-chip microcomputer) and outside (for example; Steer motor, speed motor etc.) connect, realized final control to automobile.In the present invention, the output of each sensor is as the input of the pilot model of operation on computers.
In step 302, each sensor of initialization and controller are removed the data in each sensor, and the input/output port and the register of controller is set.Because how these sensors of initialization and controller belong to the common practise of this area, so will omit initialized specific descriptions to how at this.
In step 303; Initialization clock and pilot model are (for example; Module, prediction module, comparison module, the control module etc. taken aim in advance as shown in Figure 1); Disabled interrupt in initialization procedure makes enabling time and time that automobile gets into effective stake district (as shown in Figure 4) of beginning sampling time, controller and pilot model of each sensor keep synchronously.
In step 304; Automobile goes around stake between each stake along expected trajectory (that is, serpentine path) according to the speed of setting, simultaneously the tracing sensor dynamic scan; To obtain the expected trajectory information of automobile; In scanning process, allow scanning to be interrupted by other incidents (for example, sensor fault etc.), the automotive interior sensor also writes down the state parameter (comprising yaw angle, side direction coordinate, along slope coordinate, side velocity, longitudinal velocity, side acceleration and longitudinal acceleration etc.) of automobile.Here, the speed of setting guarantees that automobile can not roll effective stake district as shown in Figure 4 away from and in testing process, keep constant in a detection circulation (the step 305-310 that describes below).
In step 305; Tracing sensor and automotive interior sensor and pilot model communicate; So that expected trajectory information and vehicle condition information are input to pilot model; In whole detection and communication process, in pilot model, opened up the information that corresponding memory headroom storage vehicle condition changes.
In step 306; Pilot model is from the prediction locus of vehicle condition information acquisition running car; Expected trajectory and prediction locus are compared parameters such as obtaining deviation (in the present invention, comprising lateral position deviation R, side acceleration, side acceleration derivative etc.).
In step 307, pilot model is utilized in the parameter (especially lateral position deviation R) that obtains in the step 306 and calculates the change amount that obtains steering wheel angle through PD control.
In step 308; Based on the detection method of pilot model change amount according to the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model; Calculate final steering wheel angle and export to automobile; Controller receives final steering wheel angle signal, according to the corresponding signal of said final steering wheel angle signal output and controlled device (for example, steer motor, speed motor etc.) with the control controlled device; Thereby accomplish corresponding operating, follow the trail of expected trajectory with Control of Automobile and go each parts of automobile.
In step 309, after controller output control signal, the required variable of the next circulation of storage in pilot model and/or controller, for example, the change amount of the steering wheel angle that in step 307, obtains etc.
In step 310, in pilot model and/or controller, after the variablees such as change amount of storage direction dish corner, determine whether to accomplish the major cycle that constitutes by step 305-309, that is, whether accomplish the required detection-comparison-control procedure of control that tracks.If accomplished detection-comparison-control procedure, then method flow advances to step 311, finishes the detection to vehicle handling stability; If do not accomplish detection-comparison-control procedure, that is, automobile is not followed the trail of serpentine path and is gone, and the control that then continues to track promptly, continues to carry out detection-comparison-control procedure.
In step 311, finish detection to vehicle handling stability.
After detecting end, according to the frequently-used data disposal route (for example, the method in the above-mentioned GB) of this area the data that in method flow, obtain are handled accordingly, thereby accomplished detection assessment vehicle handling stability.
Can find out from top description; The invention has the advantages that: proposed to utilize pilot model replace detection method that experienced driver carries out vehicle handling stability with and with the communication means of external hardware system; Whole system safety and cost are lower; Improve detection efficiency, alleviated staff's working load; Parameter through pilot model is set can the different driving styles of emulation driver's (for example, experienced driver, radical driver etc.), it is more comprehensive, reliably to make that vehicle handling stability detects, and the test duration is greatly saved; Pilot model for specific driving style is handled automobile, in the repeated detection test process, can guarantee the input of automobile consistent; Avoided system when analyzing vehicle handling stability; Input changes the influence that causes, and makes to have improved the confidence level that detects by the duplicate detection high conformity; Utilize the pilot model under the queuing network cognition system that VC++ realizes, can communicate with external hardware device easily through writing the data input/output end port.
Therefore, based on the vehicle handling stability detection method of pilot model, simple testing process, safely, save time and save money, test result is comprehensive, reliable, with a high credibility, has higher utility and meaning, is specially adapted to some Automobile Detection mechanisms.
Claims (8)
1. the vehicle handling stability detection system based on pilot model is used to detect vehicle handling stability, and said detection system comprises:
Tracing sensor is installed on the automobile, is used to carry out Path Recognition, and the output expected trajectory;
The automotive interior sensor obtains and exports vehicle condition information;
Pilot model; Comprise and take aim at module, prediction module, comparison module and control module in advance that take aim at module in advance and obtain expected trajectory according to the output that is installed in the tracing sensor on the automobile, prediction module is according to the vehicle condition information of automotive interior sensor output; Calculate the prediction locus of running car; Comparison module compares expected trajectory and prediction locus, output bias, and control module is calculated the change amount of outbound course dish corner through PD control according to said deviation; Wherein, Expected trajectory is the serpentine path on the running car path, and automobile goes around stake along serpentine path according to setting speed, and said detection system is according to the change amount of the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model; Calculate final steering wheel angle and export to automobile, follow the trail of expected trajectory with Control of Automobile and go;
Controller receives final steering wheel angle signal, exports the signal corresponding with the controlled device of automobile with the control controlled device according to said final steering wheel angle signal, thereby accomplishes the corresponding operating to each parts of automobile, and follow the trail of expected trajectory with Control of Automobile and go,
Obtain the status information of automobile after under the control of controller, operating through the automotive interior sensor, and said status information is fed back to pilot model, with the closed-loop control of realization automobile.
2. vehicle handling stability detection system according to claim 1, wherein, the speed of said setting guarantees that automobile can not roll serpentine path away from and in testing process, keep constant in a detection circulation.
3. the vehicle handling stability detection method based on pilot model is used to detect vehicle handling stability, and said method comprises:
Automobile according to the speed of setting when expected trajectory goes, be installed in tracing sensor dynamic scan on the automobile to obtain the expected trajectory information of automobile, the automotive interior sensor also writes down vehicle condition information;
Tracing sensor and automotive interior sensor and pilot model communicate, so that expected trajectory information and vehicle condition information are input to pilot model;
Pilot model is from the prediction locus of vehicle condition information acquisition running car, expected trajectory and prediction locus compared obtain deviation;
Pilot model utilizes said deviation to calculate the change amount of outbound course dish corner through PD control;
Said detection method is calculated final steering wheel angle according to the change amount of the steering wheel angle that calculates from the steering wheel angle of vehicle condition information acquisition with by pilot model, and final steering wheel angle signal is input to controller;
Controller is exported the signal corresponding with controlled device with Control of Automobile according to said final steering wheel angle signal, thereby accomplishes the corresponding operating to each parts of automobile, follows the trail of expected trajectory with Control of Automobile and goes, and detects vehicle handling stability thus,
Wherein, Pilot model comprises takes aim at module, prediction module, comparison module and control module in advance, takes aim at module in advance and obtains expected trajectory according to the output that is installed in the tracing sensor on the automobile, and prediction module is according to the vehicle condition information of automotive interior sensor output; Calculate the prediction locus of running car; Comparison module compares expected trajectory and prediction locus, output bias, and control module is calculated the change amount of outbound course dish corner through PD control according to said deviation; Expected trajectory is the serpentine path on the running car path, and automobile goes around stake along serpentine path according to the speed of setting.
4. method according to claim 3, said method also comprises: before tracing sensor and automotive interior sensor began to detect, each sensor of initialization and controller were removed the data in each sensor, and the input/output port and the register of controller is set.
5. method according to claim 4; Said method also comprises: before tracing sensor and automotive interior sensor begin to detect; Initialization clock and pilot model, the time that makes enabling time and the automobile of beginning sampling time, controller and pilot model of each sensor get into serpentine path keeps synchronously.
6. method according to claim 3, said method also comprises: after controller output control signal, the change amount of storage direction dish corner in pilot model and/or controller.
7. method according to claim 6, said method also comprises: in pilot model and/or controller, after the change amount of storage direction dish corner, determine whether to accomplish the required detection-comparison-control procedure of control that tracks.
8. method according to claim 7, said method also comprises: if accomplished detection-comparison-control procedure, then finish the detection to vehicle handling stability; If do not accomplish detection-comparison-control procedure, then continue to carry out detection-comparison-control procedure.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SU911196A1 (en) * | 1980-05-21 | 1982-03-07 | Казахский Научно-Исследовательский И Проектный Институт Автомобильного Транспорта | Device for determination of wheel machine traction and brake characteristics |
| JPH1114507A (en) * | 1997-06-19 | 1999-01-22 | Denso Corp | Vehicle simulation device |
| JP2004219338A (en) * | 2003-01-17 | 2004-08-05 | Mazda Motor Corp | Device and method of vehicle handling stability evaluation |
| CN101734252A (en) * | 2009-12-23 | 2010-06-16 | 合肥工业大学 | Preview tracking control unit for intelligent vehicle vision navigation |
| CN101842278A (en) * | 2007-11-02 | 2010-09-22 | 丰田自动车株式会社 | Vehicle control device and vehicle control method |
| CN102320301A (en) * | 2010-04-07 | 2012-01-18 | 通用汽车环球科技运作有限责任公司 | Be used to make the ride characteristic of vehicle to adapt to the method for chaufeur conversion |
-
2012
- 2012-06-29 CN CN201210219920.3A patent/CN102788704B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| SU911196A1 (en) * | 1980-05-21 | 1982-03-07 | Казахский Научно-Исследовательский И Проектный Институт Автомобильного Транспорта | Device for determination of wheel machine traction and brake characteristics |
| JPH1114507A (en) * | 1997-06-19 | 1999-01-22 | Denso Corp | Vehicle simulation device |
| JP2004219338A (en) * | 2003-01-17 | 2004-08-05 | Mazda Motor Corp | Device and method of vehicle handling stability evaluation |
| CN101842278A (en) * | 2007-11-02 | 2010-09-22 | 丰田自动车株式会社 | Vehicle control device and vehicle control method |
| CN101734252A (en) * | 2009-12-23 | 2010-06-16 | 合肥工业大学 | Preview tracking control unit for intelligent vehicle vision navigation |
| CN102320301A (en) * | 2010-04-07 | 2012-01-18 | 通用汽车环球科技运作有限责任公司 | Be used to make the ride characteristic of vehicle to adapt to the method for chaufeur conversion |
Non-Patent Citations (2)
| Title |
|---|
| TERRY D.DAY,L.DANIEL METZ: "The simulation of driver inputs using a vehicle driver model", 《2000 SOCIETY OF AUTOMOTIVE ENGINEERS》 * |
| 高振海等: "驾驶员方向控制模型及在汽车智能驾驶研究中的应用", 《中国公路学报》 * |
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